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Found 3 papers, 0 papers with code
Optimising network interactions through device agnostic models
Physically implemented neural networks hold the potential to achieve the performance of deep learning models by exploiting the innate physical properties of devices as computational tools.
Comparison of Spin-Wave Modes in Connected and Disconnected Artificial Spin Ice Nanostructures Using Brillouin Light Scattering Spectroscopy
Gaining understanding of how these very different coupling methods affect both spin-wave dynamics and magnetic reversal is key for the field to progress and provides crucial system-design information including for future systems containing combinations of connected and disconnected elements.
Quantization
Mesoscale and Nanoscale Physics
Strongly Correlated Electrons
Reconfigurable magnonic mode-hybridisation and spectral control in a bicomponent artificial spin ice
Strongly-interacting nanomagnetic arrays are finding increasing use as model host systems for reconfigurable magnonics.
Mesoscale and Nanoscale Physics Applied Physics
